#### Ran styler and fixed lints

Joshua D. Campbell authored on 06/04/2020 23:58:56
Showing 1 changed files
 ... ... `@@ -4,42 +4,43 @@` 4 4 ` # Kimberling, C. "Triangle Centers and Central Triangles." Congr.` 5 5 ` # Numer. 129, 1-295, 1998.` 6 6 ` .dist2d <- function(a, b, c) {` 7 `- v1 <- b - c` 8 `- v2 <- a - b` 9 `- m <- cbind(v1, v2)` 10 `- d <- abs(det(m)) / sqrt(sum(v1 * v1))` 11 `- return(d)` 7 `+ v1 <- b - c` 8 `+ v2 <- a - b` 9 `+ m <- cbind(v1, v2)` 10 `+ d <- abs(det(m)) / sqrt(sum(v1 * v1))` 11 `+ return(d)` 12 12 ` }` 13 13 ` ` 14 14 ` ` 15 15 ` .secondDerivativeEstimate <- function(v) {` 16 `- nv <- length(v)` 17 `- res <- rep(NA, nv)` 18 `- for (i in seq(2, nv - 1)) {` 19 `- res[i] <- v[i + 1] + v[i - 1] - (2 * v[i])` 20 `- }` 21 `- return(res)` 16 `+ nv <- length(v)` 17 `+ res <- rep(NA, nv)` 18 `+ for (i in seq(2, nv - 1)) {` 19 `+ res[i] <- v[i + 1] + v[i - 1] - (2 * v[i])` 20 `+ }` 21 `+ return(res)` 22 22 ` }` 23 23 ` ` 24 24 ` ` 25 25 ` .curveElbow <- function(var, perplexity, pvalCutoff = 0.05) {` 26 `- len <- length(perplexity)` 27 `- a <- c(var[1], perplexity[1])` 28 `- b <- c(var[len], perplexity[len])` 29 `- res <- rep(NA, len)` 30 `- for (i in seq_along(var)) {` 31 `- res[i] <- .dist2d(c(var[i], perplexity[i]), a, b)` 32 `- }` 33 `- elbow <- which.max(res)` 34 `- ix <- var > var[elbow]` 35 `- perplexitySde <- .secondDerivativeEstimate(perplexity)` 36 `- perplexitySdeSd <- stats::sd(perplexitySde[ix], na.rm = TRUE)` 37 `- perplexitySdeMean <- mean(perplexitySde[ix], na.rm = TRUE)` 38 `- perplexitySdePval <-` 39 `- stats::pnorm(perplexitySde,` 40 `- mean = perplexitySdeMean,` 41 `- sd = perplexitySdeSd,` 42 `- lower.tail = FALSE)` 43 `- # other <- which(ix & perplexitySdePval < pvalCutoff)` 44 `- return(list(elbow = var[elbow]))` 26 `+ len <- length(perplexity)` 27 `+ a <- c(var[1], perplexity[1])` 28 `+ b <- c(var[len], perplexity[len])` 29 `+ res <- rep(NA, len)` 30 `+ for (i in seq_along(var)) {` 31 `+ res[i] <- .dist2d(c(var[i], perplexity[i]), a, b)` 32 `+ }` 33 `+ elbow <- which.max(res)` 34 `+ ix <- var > var[elbow]` 35 `+ perplexitySde <- .secondDerivativeEstimate(perplexity)` 36 `+ perplexitySdeSd <- stats::sd(perplexitySde[ix], na.rm = TRUE)` 37 `+ perplexitySdeMean <- mean(perplexitySde[ix], na.rm = TRUE)` 38 `+ perplexitySdePval <-` 39 `+ stats::pnorm(perplexitySde,` 40 `+ mean = perplexitySdeMean,` 41 `+ sd = perplexitySdeSd,` 42 `+ lower.tail = FALSE` 43 `+ )` 44 `+ # other <- which(ix & perplexitySdePval < pvalCutoff)` 45 `+ return(list(elbow = var[elbow]))` 45 46 ` }`

#### fix 'stats::mean' NOTE

zhewa authored on 23/04/2019 20:13:42
Showing 1 changed files
 ... ... `@@ -34,8 +34,7 @@` 34 34 ` ix <- var > var[elbow]` 35 35 ` perplexitySde <- .secondDerivativeEstimate(perplexity)` 36 36 ` perplexitySdeSd <- stats::sd(perplexitySde[ix], na.rm = TRUE)` 37 `- perplexitySdeMean <-` 38 `- stats::mean(perplexitySde[ix], na.rm = TRUE)` 37 `+ perplexitySdeMean <- mean(perplexitySde[ix], na.rm = TRUE)` 39 38 ` perplexitySdePval <-` 40 39 ` stats::pnorm(perplexitySde,` 41 40 ` mean = perplexitySdeMean,`

#### comment out unused codes

zhewa authored on 20/04/2019 16:07:42
Showing 1 changed files
 ... ... `@@ -8,6 +8,7 @@` 8 8 ` v2 <- a - b` 9 9 ` m <- cbind(v1, v2)` 10 10 ` d <- abs(det(m)) / sqrt(sum(v1 * v1))` 11 `+ return(d)` 11 12 ` }` 12 13 ` ` 13 14 ` ` ... ... `@@ -40,6 +41,6 @@` 40 41 ` mean = perplexitySdeMean,` 41 42 ` sd = perplexitySdeSd,` 42 43 ` lower.tail = FALSE)` 43 `- other <- which(ix & perplexitySdePval < pvalCutoff)` 44 `+ # other <- which(ix & perplexitySdePval < pvalCutoff)` 44 45 ` return(list(elbow = var[elbow]))` 45 46 ` }`

#### review of reformatted files

zhewa authored on 08/04/2019 17:01:29
Showing 1 changed files
 ... ... `@@ -1,4 +1,5 @@` 1 `-# https://stackoverflow.com/questions/35194048/using-r-how-to-calculate-the-distance-from-one-point-to-a-line` 1 `+# https://stackoverflow.com/questions/35194048/using-r-how-to-calculate` 2 `+#-the-distance-from-one-point-to-a-line` 2 3 ` # http://mathworld.wolfram.com/Point-LineDistance2-Dimensional.html` 3 4 ` # Kimberling, C. "Triangle Centers and Central Triangles." Congr.` 4 5 ` # Numer. 129, 1-295, 1998.` ... ... `@@ -9,15 +10,17 @@` 9 10 ` d <- abs(det(m)) / sqrt(sum(v1 * v1))` 10 11 ` }` 11 12 ` ` 13 `+` 12 14 ` .secondDerivativeEstimate <- function(v) {` 13 15 ` nv <- length(v)` 14 16 ` res <- rep(NA, nv)` 15 `- for (i in 2:(nv - 1)) {` 17 `+ for (i in seq(2, nv - 1)) {` 16 18 ` res[i] <- v[i + 1] + v[i - 1] - (2 * v[i])` 17 19 ` }` 18 20 ` return(res)` 19 21 ` }` 20 22 ` ` 23 `+` 21 24 ` .curveElbow <- function(var, perplexity, pvalCutoff = 0.05) {` 22 25 ` len <- length(perplexity)` 23 26 ` a <- c(var[1], perplexity[1])`

#### Reformat celda_functions.R, celda_heatmap.R

ykoga07 authored on 03/04/2019 15:22:16
Showing 1 changed files
 ... ... `@@ -18,30 +18,25 @@` 18 18 ` return(res)` 19 19 ` }` 20 20 ` ` 21 `-.curveElbow <- function(var, perplexity, pval.cutoff = 0.05) {` 21 `+.curveElbow <- function(var, perplexity, pvalCutoff = 0.05) {` 22 22 ` len <- length(perplexity)` 23 `-` 24 23 ` a <- c(var[1], perplexity[1])` 25 24 ` b <- c(var[len], perplexity[len])` 26 25 ` res <- rep(NA, len)` 27 26 ` for (i in seq_along(var)) {` 28 `- res[i] <- dist2d(c(var[i], perplexity[i]), a, b)` 27 `+ res[i] <- .dist2d(c(var[i], perplexity[i]), a, b)` 29 28 ` }` 30 `-` 31 29 ` elbow <- which.max(res)` 32 30 ` ix <- var > var[elbow]` 33 `- perplexity.sde <- secondDerivativeEstimate(perplexity)` 34 `- perplexity.sde.sd <- stats::sd(perplexity.sde[ix], na.rm = TRUE)` 35 `- perplexity.sde.mean <-` 36 `- stats::mean(perplexity.sde[ix], na.rm = TRUE)` 37 `- perplexity.sde.pval <-` 38 `- stats::pnorm(` 39 `- perplexity.sde,` 40 `- mean = perplexity.sde.mean,` 41 `- sd = perplexity.sde.sd,` 42 `- lower.tail = FALSE` 43 `- )` 44 `-` 45 `- other <- which(ix & perplexity.sde.pval < pval.cutoff)` 46 `- return(list(elbow = var[elbow])) # , secondary=l[other]))` 31 `+ perplexitySde <- .secondDerivativeEstimate(perplexity)` 32 `+ perplexitySdeSd <- stats::sd(perplexitySde[ix], na.rm = TRUE)` 33 `+ perplexitySdeMean <-` 34 `+ stats::mean(perplexitySde[ix], na.rm = TRUE)` 35 `+ perplexitySdePval <-` 36 `+ stats::pnorm(perplexitySde,` 37 `+ mean = perplexitySdeMean,` 38 `+ sd = perplexitySdeSd,` 39 `+ lower.tail = FALSE)` 40 `+ other <- which(ix & perplexitySdePval < pvalCutoff)` 41 `+ return(list(elbow = var[elbow]))` 47 42 ` }`

#### Reformat plot_dr

ykoga07 authored on 02/04/2019 18:53:13
Showing 1 changed files
 ... ... `@@ -1,6 +1,7 @@` 1 1 ` # https://stackoverflow.com/questions/35194048/using-r-how-to-calculate-the-distance-from-one-point-to-a-line` 2 2 ` # http://mathworld.wolfram.com/Point-LineDistance2-Dimensional.html` 3 `-# Kimberling, C. "Triangle Centers and Central Triangles." Congr. Numer. 129, 1-295, 1998.` 3 `+# Kimberling, C. "Triangle Centers and Central Triangles." Congr.` 4 `+# Numer. 129, 1-295, 1998.` 4 5 ` .dist2d <- function(a, b, c) {` 5 6 ` v1 <- b - c` 6 7 ` v2 <- a - b`

#### Reformat elbow.R

ykoga07 authored on 02/04/2019 18:23:51
Showing 1 changed files
 ... ... `@@ -1,40 +1,46 @@` 1 1 ` # https://stackoverflow.com/questions/35194048/using-r-how-to-calculate-the-distance-from-one-point-to-a-line` 2 2 ` # http://mathworld.wolfram.com/Point-LineDistance2-Dimensional.html` 3 3 ` # Kimberling, C. "Triangle Centers and Central Triangles." Congr. Numer. 129, 1-295, 1998.` 4 `-dist2d <- function(a,b,c) {` 5 `- v1 <- b - c` 6 `- v2 <- a - b` 7 `- m <- cbind(v1,v2)` 8 `- d <- abs(det(m))/sqrt(sum(v1*v1))` 9 `-} ` 4 `+.dist2d <- function(a, b, c) {` 5 `+ v1 <- b - c` 6 `+ v2 <- a - b` 7 `+ m <- cbind(v1, v2)` 8 `+ d <- abs(det(m)) / sqrt(sum(v1 * v1))` 9 `+}` 10 `+` 11 `+.secondDerivativeEstimate <- function(v) {` 12 `+ nv <- length(v)` 13 `+ res <- rep(NA, nv)` 14 `+ for (i in 2:(nv - 1)) {` 15 `+ res[i] <- v[i + 1] + v[i - 1] - (2 * v[i])` 16 `+ }` 17 `+ return(res)` 18 `+}` 19 `+` 20 `+.curveElbow <- function(var, perplexity, pval.cutoff = 0.05) {` 21 `+ len <- length(perplexity)` 10 22 ` ` 11 `-secondDerivativeEstimate = function(v) {` 12 `- nv = length(v)` 13 `- res = rep(NA, nv)` 14 `- for(i in 2:(nv-1)) {` 15 `- res[i] = v[i+1] + v[i-1] - (2 * v[i])` 16 `- }` 17 `- return(res)` 18 `-} ` 23 `+ a <- c(var[1], perplexity[1])` 24 `+ b <- c(var[len], perplexity[len])` 25 `+ res <- rep(NA, len)` 26 `+ for (i in seq_along(var)) {` 27 `+ res[i] <- dist2d(c(var[i], perplexity[i]), a, b)` 28 `+ }` 19 29 ` ` 20 `-curveElbow = function(var, perplexity, pval.cutoff = 0.05) {` 21 `- ` 22 `- len = length(perplexity)` 23 `- ` 24 `- a = c(var[1], perplexity[1])` 25 `- b = c(var[len], perplexity[len])` 26 `- res = rep(NA, len) ` 27 `- for(i in seq_along(var)) {` 28 `- res[i] = dist2d(c(var[i], perplexity[i]), a, b)` 29 `- } ` 30 `+ elbow <- which.max(res)` 31 `+ ix <- var > var[elbow]` 32 `+ perplexity.sde <- secondDerivativeEstimate(perplexity)` 33 `+ perplexity.sde.sd <- stats::sd(perplexity.sde[ix], na.rm = TRUE)` 34 `+ perplexity.sde.mean <-` 35 `+ stats::mean(perplexity.sde[ix], na.rm = TRUE)` 36 `+ perplexity.sde.pval <-` 37 `+ stats::pnorm(` 38 `+ perplexity.sde,` 39 `+ mean = perplexity.sde.mean,` 40 `+ sd = perplexity.sde.sd,` 41 `+ lower.tail = FALSE` 42 `+ )` 30 43 ` ` 31 `- elbow = which.max(res)` 32 `- ix = var > var[elbow]` 33 `- perplexity.sde = secondDerivativeEstimate(perplexity)` 34 `- perplexity.sde.sd = stats::sd(perplexity.sde[ix], na.rm=TRUE)` 35 `- perplexity.sde.mean = stats::mean(perplexity.sde[ix], na.rm=TRUE)` 36 `- perplexity.sde.pval = stats::pnorm(perplexity.sde, mean=perplexity.sde.mean, sd=perplexity.sde.sd, lower.tail = FALSE) ` 37 `- ` 38 `- other = which(ix & perplexity.sde.pval < pval.cutoff)` 39 `- return(list(elbow=var[elbow]))#, secondary=l[other]))` 44 `+ other <- which(ix & perplexity.sde.pval < pval.cutoff)` 45 `+ return(list(elbow = var[elbow])) # , secondary=l[other]))` 40 46 ` }`

#### Add function definition for sd,pnorm,median

Yusuke Koga authored on 26/03/2019 21:23:14
Showing 1 changed files
 ... ... `@@ -31,9 +31,9 @@ curveElbow = function(var, perplexity, pval.cutoff = 0.05) {` 31 31 ` elbow = which.max(res)` 32 32 ` ix = var > var[elbow]` 33 33 ` perplexity.sde = secondDerivativeEstimate(perplexity)` 34 `- perplexity.sde.sd = sd(perplexity.sde[ix], na.rm=TRUE)` 35 `- perplexity.sde.mean = mean(perplexity.sde[ix], na.rm=TRUE)` 36 `- perplexity.sde.pval = pnorm(perplexity.sde, mean=perplexity.sde.mean, sd=perplexity.sde.sd, lower.tail = FALSE) ` 34 `+ perplexity.sde.sd = stats::sd(perplexity.sde[ix], na.rm=TRUE)` 35 `+ perplexity.sde.mean = stats::mean(perplexity.sde[ix], na.rm=TRUE)` 36 `+ perplexity.sde.pval = stats::pnorm(perplexity.sde, mean=perplexity.sde.mean, sd=perplexity.sde.sd, lower.tail = FALSE) ` 37 37 ` ` 38 38 ` other = which(ix & perplexity.sde.pval < pval.cutoff)` 39 39 ` return(list(elbow=var[elbow]))#, secondary=l[other]))`

#### Merging from compbiomed@devel

Sean Corbett authored on 18/03/2019 22:09:34
Showing 0 changed files

#### Elbow method for choosing K/L from perplexity curve

Sean Corbett authored on 08/03/2019 16:53:45
Showing 1 changed files
 1 1 `new file mode 100644` ... ... `@@ -0,0 +1,40 @@` 1 `+# https://stackoverflow.com/questions/35194048/using-r-how-to-calculate-the-distance-from-one-point-to-a-line` 2 `+# http://mathworld.wolfram.com/Point-LineDistance2-Dimensional.html` 3 `+# Kimberling, C. "Triangle Centers and Central Triangles." Congr. Numer. 129, 1-295, 1998.` 4 `+dist2d <- function(a,b,c) {` 5 `+ v1 <- b - c` 6 `+ v2 <- a - b` 7 `+ m <- cbind(v1,v2)` 8 `+ d <- abs(det(m))/sqrt(sum(v1*v1))` 9 `+} ` 10 `+` 11 `+secondDerivativeEstimate = function(v) {` 12 `+ nv = length(v)` 13 `+ res = rep(NA, nv)` 14 `+ for(i in 2:(nv-1)) {` 15 `+ res[i] = v[i+1] + v[i-1] - (2 * v[i])` 16 `+ }` 17 `+ return(res)` 18 `+} ` 19 `+` 20 `+curveElbow = function(var, perplexity, pval.cutoff = 0.05) {` 21 `+ ` 22 `+ len = length(perplexity)` 23 `+ ` 24 `+ a = c(var[1], perplexity[1])` 25 `+ b = c(var[len], perplexity[len])` 26 `+ res = rep(NA, len) ` 27 `+ for(i in seq_along(var)) {` 28 `+ res[i] = dist2d(c(var[i], perplexity[i]), a, b)` 29 `+ } ` 30 `+` 31 `+ elbow = which.max(res)` 32 `+ ix = var > var[elbow]` 33 `+ perplexity.sde = secondDerivativeEstimate(perplexity)` 34 `+ perplexity.sde.sd = sd(perplexity.sde[ix], na.rm=TRUE)` 35 `+ perplexity.sde.mean = mean(perplexity.sde[ix], na.rm=TRUE)` 36 `+ perplexity.sde.pval = pnorm(perplexity.sde, mean=perplexity.sde.mean, sd=perplexity.sde.sd, lower.tail = FALSE) ` 37 `+ ` 38 `+ other = which(ix & perplexity.sde.pval < pval.cutoff)` 39 `+ return(list(elbow=var[elbow]))#, secondary=l[other]))` 40 `+}` 0 41 `\ No newline at end of file`

#### Fixed error in example code for reursive split and removed export of curve elbow until we know we want to use it

Joshua D. Campbell authored on 08/03/2019 16:15:10
Showing 1 changed files
 ... ... `@@ -17,7 +17,6 @@ secondDerivativeEstimate = function(v) {` 17 17 ` return(res)` 18 18 ` } ` 19 19 ` ` 20 `-#' @export` 21 20 ` curveElbow = function(var, perplexity, pval.cutoff = 0.05) {` 22 21 ` ` 23 22 ` len = length(perplexity)`

#### Replace set.seed() with setSeed(). Fixes #37

Sean Corbett authored on 24/02/2019 22:33:31
Showing 1 changed files
 1 1 `new file mode 100755` ... ... `@@ -0,0 +1,41 @@` 1 `+# https://stackoverflow.com/questions/35194048/using-r-how-to-calculate-the-distance-from-one-point-to-a-line` 2 `+# http://mathworld.wolfram.com/Point-LineDistance2-Dimensional.html` 3 `+# Kimberling, C. "Triangle Centers and Central Triangles." Congr. Numer. 129, 1-295, 1998.` 4 `+dist2d <- function(a,b,c) {` 5 `+ v1 <- b - c` 6 `+ v2 <- a - b` 7 `+ m <- cbind(v1,v2)` 8 `+ d <- abs(det(m))/sqrt(sum(v1*v1))` 9 `+} ` 10 `+` 11 `+secondDerivativeEstimate = function(v) {` 12 `+ nv = length(v)` 13 `+ res = rep(NA, nv)` 14 `+ for(i in 2:(nv-1)) {` 15 `+ res[i] = v[i+1] + v[i-1] - (2 * v[i])` 16 `+ }` 17 `+ return(res)` 18 `+} ` 19 `+` 20 `+#' @export` 21 `+curveElbow = function(var, perplexity, pval.cutoff = 0.05) {` 22 `+ ` 23 `+ len = length(perplexity)` 24 `+ ` 25 `+ a = c(var[1], perplexity[1])` 26 `+ b = c(var[len], perplexity[len])` 27 `+ res = rep(NA, len) ` 28 `+ for(i in seq_along(var)) {` 29 `+ res[i] = dist2d(c(var[i], perplexity[i]), a, b)` 30 `+ } ` 31 `+` 32 `+ elbow = which.max(res)` 33 `+ ix = var > var[elbow]` 34 `+ perplexity.sde = secondDerivativeEstimate(perplexity)` 35 `+ perplexity.sde.sd = sd(perplexity.sde[ix], na.rm=TRUE)` 36 `+ perplexity.sde.mean = mean(perplexity.sde[ix], na.rm=TRUE)` 37 `+ perplexity.sde.pval = pnorm(perplexity.sde, mean=perplexity.sde.mean, sd=perplexity.sde.sd, lower.tail = FALSE) ` 38 `+ ` 39 `+ #other = which(ix & perplexity.sde.pval < pval.cutoff)` 40 `+ return(list(elbow=var[elbow])) #, secondary=l[other]))` 41 `+}`